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On deformable models for visual pattern recognition
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DOI：10.1016/S0031-3203(01)00135-2.png)
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Abstract
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This paper reviews model-based methods for non-rigid shape recognition. These methods model, match and classify non-rigid shapes. which are generally problematic for conventational algorithms using rigid models. Issues including model representation, optimization criteria formulation, model matching, and classification are examined in detail with the objective to provide interested researchers a roadmap for exploring the field. This paper emphasizes on 2D deformable models. Their potential applications and future research directions, particularly on deformable pattern classification, are discussed. (C) 2002 Published by Elsevier Science Ltd on behalf of Pattern Recognition Society.
Keywords:
deformable models
model representation
criteria formulation
matching
classification
topology adaptation
regularization
optimization
initialization
constraint incorporation
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